This project is a web application built with Flask and a deep learning model to distinguish between real images (captured by cameras) and fake images (generated using GANs). Users can upload an image, and the app will predict whether the image is real or fake, displaying the result along with a preview of the uploaded image.

This project involves building a sentiment analysis model for an e-commerce platform. The goal is to predict the binary rating (positive or negative) of product reviews based on their text data. The model uses machine learning techniques to classify reviews and provides a submission-ready CSV file for evaluation.

This project builds a predictive model to help HR teams proactively manage employee attrition. By understanding the key factors influencing attrition, the company can take steps to reduce turnover and its associated costs.

This project demonstrates a time-series forecasting problem where historical sunspot data is used to predict future sunspot activity. By accurately predicting sunspot counts, we can prepare for potential disruptions caused by solar activity.